Stochastic modelling of signal transduction in olfactory neurons
| Authors | |
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| Year of publication | 2010 |
| Type | Article in Proceedings |
| Conference | 6th Summer School on Computational Biology |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.iba.muni.cz/summer-school2010/ |
| Field | General mathematics |
| Keywords | sensory neurons;stochastic modelling;steady state |
| Description | Several models of olfactory sensory neurons (concentration detectors, flux detectors) are investigated. Their behavior is described by stochastic processes of binding and activation. The models assume that the response, concentration of activated receptors, is determined by the signal, fixed log-concentration of odorant in perireceptor space. An approach used is based on stochastic variant of the law of mass action as a neuronal model. The statistical steady-state characteristics of the models are derived. |
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